Visualizing and Managing Folksonomies, SASWeb 2011 workshop, at UMAP 2011


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Visualizing and Managing Folksonomies, SASWeb 2011 workshop, at UMAP 2011

  1. 1. Visualizing and Managing Folksonomies Antonina Dattolo { Emanuela PitassiUniversity of Udine, Via delle Scienze 206, I-33100 Udine, Italy June 25, 2011
  2. 2. Outline Background Open Issues Our Proposal Folkview: the formal model Folkview views and authoring Related works Conclusion and future work
  3. 3. Background I The advent of Web 2.0 shifts the task of classifying resources from a reduce set of experts, to the wide set of Web users. I Free classi
  4. 4. cations are made by user thanks to tags, which generate a folksonomy (Vander Wal, 2004; Mathes, 2004) I Several social tagging systems such as Bibsonomy (Hotho et al, 2006) or delicious allow users to classify resources and generate folksonomies, but they are dicult to manage, modify and visualize in dynamic and personalized ways.
  5. 5. Background: some examples I The creation of personalized views, which may display a limited, well de
  6. 6. ned and personalized sub-portion of an entire hyperspace has already been considered in dierent settings. I Adptive bookmarking systems, e.g.: I PowerBookmarks (Li et al, 1999) I Siteseer (Rucker et al, 1997) I Web Tagger (Keller et al, 1997) I Start pages on Web browser, e.g.: I Netvibes ( I My Yahoo ( I iGoogle (
  7. 7. Open Issues I Social Tagging Systems suer from dierent issues: I the lack and the exigence of general methotodologies for extracting semantic information (Dattolo et al., 2010) I the lack and the exigence of personalized and dynamic workspaces in wich users I Can visualize personalized views of the folksonomy I Can apply personal changes I A crucial task for developers of current Web application is how to model and create speci
  8. 8. c tools for providing personalized views to the users.
  9. 9. Open Issues I A folksonomy is usually represented by a tripartite graph or network Various researches have dealt with the issue related to the complexity of the nature of the graph itself, projecting a folksonomy on simpli
  10. 10. ed structures (Lambiotte, 2006; Dattolo, 2011). I Generally a folksonomy is represented by a tag-cloud, but this kind of visualization is not sucient as the sole means of navigation (Sinclair, 2007). I Possible multiple visualizations of a folksonomy allow users to: I have a more eective comprehension of the semantic relations of a folksonomy I have a more useful navigation through the involved elements I manipulate the existing relations among tags and resources according to the user needs.
  11. 11. Our Proposal I The main aim of this work is to propose and describe a novel, distributed, modular system called Folkview, whereby a folksonomy is conceived dynamically through the use of multiple agents. I These agents will be capable of I managing the structural and semantic properties; I cooperating for obtaining common objectives; I oering personalized and dynamic views. I Steps: I De
  12. 12. nition of the Formal Model which exploits multi-agents system I Personalized views Folkview Prototype
  13. 13. The formal model I Traditionally, given the sets of users U , tags T and and resources R , a folksonomy is de
  14. 14. ned as the set of tag assignments (u ; r ; t ) P U ¢ T ¢ R i j k where i = 1; : : : ; jU j; j = 1; : : : ; jT j; k = 1; : : : ; jR j, each of them indicating that user u has tagged the resource r with i j t . k I User pro
  15. 15. les, functions, metrics or semantic relations among users, tags, resources and tas are not intrinsic properties of the folksonomy.
  16. 16. The structural components of the folksonomy I In order to de
  17. 17. ne a F , we identify three classes of sets: I T 2 T is the set of tags used by u on r ; ui ;rj i j I R 2 R is the set of resources tagged by u with t ; ui ;tk i k I U is the set of users that tagged r with t . tk ;rj j k I Each set represents a structural component of the folksonomy, and we call it structural ; the tags are grouped associating to them a semantic label for identifying their meaning in that dimension.
  18. 18. Our representation of a folksonomy Figure: 6 structural dimensions (left) and the corresponding folksonomy (right) The
  19. 19. gure above represents three linear paths that contain the resources tagged by user u , using respectively t , t and t . 1 1 2 3 The labels associated with them are respectively u ; t , u ; t and 1 1 1 2 u ; t , and represent a sub-portion of her personomy. 1 3
  20. 20. De
  21. 21. nition of Structural Dimension and Static Folksonomy De
  22. 22. nition A structural dimension is a labeled path Dui ;rj = (V ; E ; ) where I V =T is the set of vertices, ui ;rj I E is the set of edges, I (e ) = (u ; r ) Ve P E is an edge labeling, and degree (t ) = 0; 1; 2 Vt P T i j k . k ui ;rj In particular, degree (t ) = 0; 1; 2 only if jT j = 1. k ui ;rj De
  23. 23. nition A static folksonomy F is a labeled multigraph given by the union of three families of structural dimensions. F = [ Dui ;rj ‘ [ Dui ;tk ‘ [ Dtk ;rj i ;k i ;j j ;k
  24. 24. A dimension as an agent We can introduce the de
  25. 25. nition of the dimension h ui ; r j based on the structural dimension D . ui ;rj De
  26. 26. nition A dimension h = (Ts ; En; Re ; Ac ) is an agent where I Ts = D ; ui ;rj I En = fu ; r ; t ; : : : ; t g; i j 1 n I Re = fYg, initially; I Ac = fadd -tag ; delete -tag ; modify -tag ; : : : g Analogously, we can de
  27. 27. ne new classes of agent dimensions, not only for structural dimensions. New dimensions can be created directly from the user, or computed by the system applying speci
  28. 28. c metrics, or generated applying ontological models: I each dimension can contain other dimensions; dimension associates a semantics to the set of grouped entities.
  29. 29. Folksonomy de
  30. 30. nition as a multi-agent system De
  31. 31. nition A folksonomy F is a multi-agent system formally described as a labeled multigraph of agent entities, organized in semantic contexts, called dimensions. p= [h n i i =1 All in a folksonomy is a computational agent, equipped with a set of local variables, that de
  32. 32. ne its internal state, and a modular and extensible set of procedural skills.
  33. 33. Folkview views and authoring In the labeled multigraph contained in the de
  34. 34. nition of p we can recognize the zz-structures (Nelson, 2004): they are non-hierarchical, minimalist, scalable structure for storing, linking and manipulating dierent kind of data. From these structures, we inherit many strengths, such as their intrinsic capability to preserve contextual interconnections among dierent information, thanks to their particular properties.
  35. 35. Folkview views and authoring In the
  36. 36. gure the presence of a black triangle symbol, in two positions, correspond to selected/not selected : these triangles are associated to scripts related to the session agent of the current visualization, and represent the mean to interact with the cell-agent. When selected, the session agent asks to the chosen resource (r , 9 in our example) the set of actions Ac that can be activated on it. Then r sends a multicast message to all the dimensions in 9 which it is included, and a run-time created contextual menu, organized in three meta-categories (views, metrics and semantics) is shown. I The
  37. 37. rst category menu is concerning the dierent kinds of possible views I The other two categories of functions oered by the menu, are related to: I the computation of an extensible set of metrics , I the application of opportune semantic relations and ontologies in order to generate, for example, speci
  38. 38. c recommendations on
  39. 39. Related works I Few works have addressed the problem of interactive visualizations of folksonomies: I customized cluster maps for visualizing both the overview and the detail of semantic relationships intrinsic in the folksonomy (Montero et al., 2007); I using information visualization techniques (IF) to discover implicit relationships between users, tags and bookmarks, end-users have dierent ways to discover content and information otherwhise dicult to understand (Klerx and Duval, 2009) I the TagGraph project ( is a folksonomy navigator which visualizes the relationships between Flickr tags. I Nevertheless these works do not provide neither personalized views nor eective dynamic changes according to the user needs or preferences.
  40. 40. Conclusion and future work I We have proposed an innovative way to conceive a folksonomy in terms of a multi-agent system,
  41. 41. rst de
  42. 42. ning a formal model and then showing Folkview. I We have built a partial, but modular and extensible, prototype, based on a public dataset taken from delicious, and that implements the structural aspects of the considered folksonomy. I As future work we want to extend the prototype: I to all the main functionality we discussed, focusing our attention on a semantic personalization; I to extract data from a large number of social tagging systems.